Expression patterns of small numbers of transcripts from functionally-related pathways predict survival in multiple cancers.
BMC Cancer
; 19(1): 686, 2019 Jul 12.
Article
em En
| MEDLINE
| ID: mdl-31299925
ABSTRACT
BACKGROUND:
Genetic profiling of cancers for variations in copy number, structure or expression of certain genes has improved diagnosis, risk-stratification and therapeutic decision-making. However the tumor-restricted nature of these changes limits their application to certain cancer types or sub-types. Tests with broader prognostic capabilities are lacking.METHODS:
Using RNAseq data from 10,227 tumors in The Cancer Genome Atlas (TCGA), we evaluated 212 protein-coding transcripts from 12 cancer-related pathways. We employed t-distributed stochastic neighbor embedding (t-SNE) to identify expression pattern difference among each pathway's transcripts. We have previously used t-SNE to show that survival in some cancers correlates with expression patterns of transcripts encoding ribosomal proteins and enzymes for cholesterol biosynthesis and fatty acid oxidation.RESULTS:
Using the above 212 transcripts, t-SNE-assisted transcript pattern profiling identified patient cohorts with significant survival differences in 30 of 34 different cancer types comprising 9350 tumors (91.4% of all TCGA cases). Small subsets of each pathway's transcripts, comprising no more than 50-60 from the original group, played particularly prominent roles in determining overall t-SNE patterns. In several cases, further refinements in long-term survival could be achieved by sequential t-SNE profiling with two pathways' transcripts, by a combination of t-SNE plus whole transcriptome profiling or by employing t-SNE on immuno-histochemically defined breast cancer subtypes. In two cancer types, individuals with Stage IV disease at presentation could be readily subdivided into groups with highly significant survival differences based on t-SNE-based tumor sub-classification.CONCLUSIONS:
t-SNE-assisted profiling of a small number of transcripts allows the prediction of long-term survival across multiple cancer types.Palavras-chave
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Transdução de Sinais
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Biomarcadores Tumorais
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Regulação Neoplásica da Expressão Gênica
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Transcriptoma
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Neoplasias
Tipo de estudo:
Prognostic_studies
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Risk_factors_studies
Limite:
Female
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Humans
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Male
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article